Conventional computing and electronic devices enable a user to input a choice or a selection in different ways. For example, a user can employ an alphanumeric keyboard, a cursor control device or a microphone to indicate a choice or selection. Moreover, capacitive sensing devices can be also used to provide an input selection to a computing device or other types of electronic devices.
A capacitive sensing device can include a number of capacitive sensor channels. More specifically, capacitive sensing devices are typically composed of some combination of capacitive components such as, for example, capacitive buttons, capacitive sliders or wheels, and capacitive pads. Each of these components is, in turn, composed of one or more individual capacitive sensor channels which must have their individual sensitivities tuned for the application and/or embodiment for which they are currently being designed. Hence, when developing a capacitive sensing device, one of the key tasks is to determine the proper sensitivity settings for each capacitive sensor channel.
Conventional methods of determining the proper sensitivity settings for capacitive sensor channels have been aimed at adjusting the sensitivity settings based upon a nominal (i.e., average or typical) capacitive sensing device. In actual use, however, tuning sensitivity settings for capacitive sensor channels based upon a nominal capacitive sensing device is not the optimal overall solution for mass production. That is, in mass production, the sensor channel (or sensor channels) on one capacitive sensing device will not have the same sensitivity value as the sensor channel (or sensor channels) on a different capacitive sensing device built in the same mass production process. Variations in plastic cover thickness, adhesive thickness and uniformity, capacitive sensor geometry, electronic variation, and numerous other sources will result in the capacitive sensing devices having variations in their respective sensor channel sensitivity values. More specifically, in a typical mass production process, the individual sensor channels will have variations in their respective sensitivity values about an average sensitivity value. As a result, unless each individual sensor channel of each capacitive sensing device produced in the same mass production process is individually adjusted to reproduce the same sensitivity value, a distribution of sensitivity values will occur across the sensor channels of the capacitive sensing devices produced in the mass production process.
The conventional methods for determining proper sensor channel sensitivity settings for mass produced capacitive sensing devices typically attempt to choose the most average or typical capacitive sensing device (sometimes called a “golden board”). This particular golden board is then used as a standard for tuning the sensitivity settings of other capacitive sensing devices manufactured in the same mass production process. Such an approach has drawbacks associated therewith. As an example, in a reasonable sample size of candidate capacitive sensing devices, it is highly unlikely that on a single capacitive sensing device each sensor channel will exhibit the average or nominal sensitivity value. For example, on a single capacitive sensing device having multiple sensor channels, a first sensor channel may exhibit a sensitivity value at or near the nominal sensitivity value for that particular sensor channel. However, on the same single capacitive sensing device, a second sensor channel may exhibit a sensitivity value quite different from the nominal sensitivity value for that particular sensor channel. Hence, when considering only the first sensor channel, the single capacitive sensing device may be appropriate to use as the golden board for the first sensor channel. At the same time, however, when considering only the second sensor channel, the single capacitive sensing device is not appropriate to use as the golden board for the second sensor channel. Even when a best choice is made by choosing a golden board by using a weighting algorithm which favors overall conformance to the average, one or more individual sensor channels of the chosen golden board may still vary significantly from the average sensitivity value for those one or more individual sensor channels.
As yet another drawback, even when using a mass production process, it may be necessary or desirable to choose production sensitivities using a relatively small number of prototype capacitive sensing devices. In such a circumstance, due to the relatively small number of capacitive sensing devices manufactured (i.e., the small sample size), it may not be possible to find an individual board with all channels sufficiently near the average. Therefore, the selection of an appropriate golden board becomes less obvious, and the relative importance of the golden board as a standard for tuning of other capacitive sensing devices is compromised.
Accordingly, a method and apparatus for enabling the tuning of a capacitive sensing device, but wherein the method and apparatus avoid the drawbacks mentioned above, would be advantageous.